AI early warning system for zoonotic diseases to be deployed
What's the story
In a major development, the Indian government is leveraging artificial intelligence (AI) to build an early warning system for zoonotic diseases. The project, led by the Indian Council of Medical Research (ICMR) under the National One Health Mission (NOHM), aims to detect emerging pathogens that jump from animals to humans. It is a proactive approach toward disease surveillance, targeting threats such as Nipah virus, Zika, Avian Influenza (H5N1), and Kyasanur Forest Disease.
Project goals
The AI system will provide early signal detection
The AI system will offer early signal detection and real-time decision support to prevent local outbreaks from escalating into pandemics. It will employ advanced data analytics, including predictive modeling, automated disease surveillance, and rapid response coordination. The government is expanding its digital and physical infrastructure to manage high-resolution health data for this purpose.
Data management
Strengthening public health infrastructure
The Integrated Health Information Platform (IHIP) offers a unified and near-real-time reporting system across all 36 states and Union territories. The Ayushman Bharat Digital Mission (ABDM) has built a national digital health ecosystem that integrates various health programs. This enables the creation of digitized records usable for predictive analytics and rapid response, thus strengthening India's public health infrastructure against future pandemics.
Technological advancement
ICMR invites EoIs from eligible organizations
The ICMR has invited Expressions of Interest (EoI) from eligible organizations, including academic institutions, professional bodies, universities, and NGOs. These entities will develop AI-enabled tools that can identify 'early signals' of novel pathogens across human, animal, and environmental sectors. The scope of work is comprehensive as it requires organizations to design these tools and integrate them for end-users while also undertaking passive evaluations at every stage of development.
Surveillance improvement
Expert opinion on the matter
Dr. Kunal Sharma, VP of Integrated Oncopathology and AI initiatives at Agilus Diagnostics, explained that AI strengthens disease surveillance by turning scattered signals into actionable early warnings. "By combining human, animal, and environmental data, it can spot unusual patterns—fever clusters, lab positives, vector changes or livestock deaths—far earlier than manual systems," he said. Predictive models help estimate where an outbreak may spread next, while automated dashboards support faster decisions on testing containment and resource deployment.